Subband coding with pitchband predictive coding in each subband

Abstract: A filterbank (FA) breaks down the digital audio signal into a plurality of frequency subbands (SB), from which respective predictions are subtracted in an adder (SO1). The residues of the substraction are requantized in a quantizer (QU) under control of a bit allocator (BA) governed by a predetermined perceptual model in order to remove irrelevant information from the subband signals. The predictions are generated by circuit means (IQ, IS, CP, PR) based on the output signals from the quantizer, as a weighted average, by means of prediction coefficients (PCT), of a plurality of samples preceding in time by a delay interval (D) chosen for each subband within a time window. A formatter (FT) packs into frames the output signals of the quantizer together with the value of the delay interval.

Description: This invention is concerned with a process for encoding digital audio signals by separating the signals into subbands, and also with a device for implementing the process. As known, a digital audio signal comprises one, two, or several bitstreams, known as audio channels and containing the sound information, according to whether the signal is monophonic, stereophonic or multiphonic (or multichannel). The bitstreams comprising the signals are all sampled at the same sampling rate: according to Recommendation 646 of ITU-R, this rate can be chosen among the values 32 kHz, 44,1 kHz and 48 kHz, the last being generally used in professional environments. Each sample may be quantized with a variable number of bits, depending on the application. If the maximum volume range perceivable by the human ear is desired, then the samples should be quantized with at least 16 bits. Therefore, assuming a sampling rate of 48 kHz and a 16-bit quantization, a monophonic signal would need a continuous bitstream of 768 kbit/s in transmission. This value must be multiplied by the number of channels, if the signal is multichannel. One can see that the transmission of those signals would require transmission channels of a very large capacity, generally larger than the capacity of conventional radio broadcasting channels, and so than the capacity of signal storage media, such as magnetic tapes for nonprofessional use. Accordingly, in order to reduce the bitrates of such digital audio signals without appreciably degrading the sound quality from the standpoint of human perception, it is known to break down the signal into frequency subbands by means of a digital filterbank and to quantize the signal contained in each subband, using information obtained from a perceptual analysis of the signal, based on a model that, by simulating the behaviour of the human ear, determines at all instants which is the perceivable volume range in each frequency subband. A band reduction method of this kind is disclosed, for instance, in Y.F. Dehery, G. Stoll, L.v.d. Kerkhof, "MUSICAM Source Coding for Digital Sound", EBU Technical Review, No. 237. Such coding, as shown by B.C.J. Moore, "An Introduction to the Psychology of Hearing", Academic Press, London, can remove from the original signal all information that, due to physiologic reasons, does not contribute to the perception of the sound, and which, accordingly, is termed irrelevant. In order to carry out the above perceptual analysis, the signal is subdivided in windows of constant duration, generally of 10 to 20 ms, which are called frames. The bitstream generated by the encoding of one frame may be constant or not, but, since most available transmission channels require a constant-speed bitstream, where the coding of a frame does not generate a constant quantity of bits, a buffer is used, which fills up at a variable speed and empties at constant speed. In any case, the speed of the bitstream from the coder must be matched to the channel speed, in order to avoid information loss and consequently errors in decoding. Since the amount of bits required for encoding an audio frame transparently, i.e. without causing audible degradation of the signal, varies as a function of the signal itself, when channels of limited capacity are used, such as in commercial broadcasting or in storing the signal upon a magnetic or optical support, the subband samples may turn out to be quantized with a number of bits which is smaller than required by the perceptual analysis, so that a perceivable quantization noise is created. In order to reduce the redundancy of a generic digital signal, a technique has also been proposed which is known as ADPCM (Adaptive Differential Pulse Code Modulation), e.g. as disclosed in J.G. Proakis, "Digital Communications", McGraw-Hill, New York. In this technique, a signal sample entering the encoder is compared with a sample immediately preceding in time (or with a weighted average of several immediately preceding samples), and the residue, or difference, between the actual sample and its prediction is applied to the quantizer. For a better correction, the prediction is reconstructed from the output of the encoder, using prediction coefficients that are developed as also taught by Proakis, op. cit. The above ADPCM technique has been successfully applied to video signals, where signal samples which are close in time or in space are often almost identical (quasi static images or areas of quasi uniform color), and therefore give rise to residues close to zero. However, the technique is ineffective for audio signals, because they comprise rapidly changing, indeed oscillating, waveshapes, which would give rise to mostly large residues, having an information content not less than that of the original signal. The main object of the invention is therefore to provide a process for encoding a digital audio signal, as well as a coder for implementing it, such as to reduce the bitstream generated in the coding process, without increasing the quantization noise in the subband samples for a wide class of audio signals, while providing a performance not worse than the known processes with signals not belonging to that class. The invention attains the above and other objects and advantages, such as will appear from the following disclosure, by a process for encoding an input digital audio signal by breaking it down into a plurality of frequency subbands and requantization according to a predetermined perceptual model, and for delivering an output digital audio signal in form of a sequence of frames, each containing information on the course of each subband within a predetermined time window, characterized in that residues are formed by subtracting from said subbands, in each window, respective predictions, said respective predictions are reconstructed from the requantized signals by means of a weighted average of a plurality of samples preceding in time by respective delay intervals, chosen for each subband, said residues formed are requantized and said requantized residues and said prediction coefficients are packed together into said frames. The invention also provides an encoder for digital audio signals, including a filterbank for breaking down said digital audio signals into a plurality of frequency subbands, a quantizer for receiving subband signals and requantizing them under control of a bit allocator governed by a predetermined perceptual model in order to remove irrelevant information from the subband signals, and a formatter which receives the quantizer's output signals and packs them in frames, characterized in that the encoder further includes circuit means for receiving the quantizer's output and reconstructing predictions of the current sample as a weighted average of a plurality of samples preceding in time by a delay interval chosen for each subband within a window, and an adder receiving the outputs of the breakdown filterbank and the predictions and generating a residue as difference which is fed to the quantizer, and in that said formatter includes the value of said delay interval in the frames. The invention will now be described in more detail with reference to a few preferred embodiments, which are shown in the attached drawings, and which are given by way of illustrative and nonlimiting example: Fig. 1 is a block diagram of a subband encoder for digital audio signals according to the prior art; Fig. 2 is a block diagram of a decoder of the prior art, for operation in association with the encoder of Fig. 1; Fig. 3 is a block diagram of a subband encoder according to a first preferred embodiment of the invention; Fig. 4 is a block diagram of a decoder for operation in association with the encoder of Fig. 3; Fig. 5 shows the operation of predictor PR in the encoder of Fig. 4; Fig. 6 is a block diagram of a subband encoder according to a second preferred embodiment of the invention; Fig. 7 is a block diagram of a decoder for operation in association with the encoder of Fig. 6; Fig. 8 is a modification of the encoder of Fig. 6; and Fig. 9 is a modification of the decoder of Fig. 7. With reference to Fig. 1, in a typical subband encoder without an output buffer, shown by way of example, a digital audio signal SIG is subdivided in 24-ms windows, and each window is encoded according to the following process. Signal SIG is fed to an analyzing filterbank FA, which converts it into a signal SB comprising 32 components, each component containing the portion of signal SIG which falls within a given frequency subband. The choice of 32 subbands, while typical, is given by way of example, the number of components, as well as the window size, being open to arbitrary choice. Block CS sets for each subband suitable scalefactors for normalizing signal SB, as known to the person skilled in the art. The normalization operation consists in shifting the signal to maximum admissible level, by multiplication by a suitable scalefactor. This operation is necessary in order to obtain the best advantage from the levels available after quantization. After normalization in block SC, signal SB is fed to a quantizer QU, and gives rise to an output signal RSB. Concurrently, signal SIG is fed to a circuit block MP, which, on the basis of a predetermined perceptual model, e.g. as defined in ISO-IEC International Standard 11172-3, determines the volume range that each subband is to have for the added quantization noise not to be perceivable. Circuit MP controls a bit allocator BA, which determines, from the available number of bits and the information received from the perceptual model, how many bits should be allocated to the samples in each subband, and drives quantizer QU accordingly, through a signal BAT. Finally, a formatting circuit block FT assembles the frame, which is then sent to the transmission channel. The frame should contain the bit allocation signal BAT, the scalefactors SCT, and obviously the audio samples RSB from subbands SB. The transmitted stream therefore comprises a continuous sequence of frames, each containing the information necessary to reconstruct 24 ms of audio. An associated decoder, shown on Fig. 2, inverts the operations of formatting (IF), quantization (IQ) and scaling (IS), respectively, the resulting signal PCM being reconstructed by synthesizing filter FS. The above example, for simplicity, refers to a coder device for a monophonic signal; for a multichannel signal, each channel should be processed separately by a device as described. Portions of the encoding may also be made conjointly on all audio channels, in order to reduce the inter-channel redundancy and to optimize the bit allocation; the fundamental pattern, however, remains unchanged. Fig. 3 shows a block diagram of a subband encoding system similar to the system of Fig. 1, which has been improved according to a preferred embodiment of the invention. The system comprises the same blocks and operative connections of Fig. 1, but it further incorporates a redundancy reduction system which is based on prediction. The system is similar to what is known as ADPCM, but is modified as described below, for use with audio signals. According to the above operational principle, instead of signal SB being fed to quantizer QU directly, in the inventive system the subband signals SB are compared with respective reconstructed samples, or predictions, PRC, thus obtaining difference signals, or residues, which are themselves fed to the quantizer. The reconstructed samples, according to the invention, belong to a time instant preceding the instant of the current sample by a variable time (or number of samples), which is determined in each case so that the residue is minimized. The choice of the delay is based on the assumption, which is valid in many cases and certainly for musical signals, that the subband signals have quasi-periodic patterns: it is then advantageous to choose a time delay equal to the pseudo-period (or possibly half the pseudoperiod) of the subband signal in the window that is processed at that time. An adder SO1 then computes the prediction error between the sample SB and the prediction PRC of that sample (described below), giving rise to an output residue RES. Residue RES, through a switch SW1, is then normalized in a scaling circuit SC and is quantized in the quantizer QU, identically to Fig. 1. Signal RSB at the output of quantizer QU is subjected to inverse quantization in a block IQ, to denormalization in a block IS, and finally to reconstruction of the original signal in a second adder SO2, which adds together the predicted component and the transmitted component, to deliver a co-decoded version, which is loaded to a memory MF through a switch SW2. The co-decoded version is fed by memory MF, together with signal SB, to a block CP which computes prediction coefficients PCT and feeds them to a predictor PR for calculation of the prediction. The predictor feeds to adder SO1 the above mentioned prediction. The prediction coefficients PCT are, in practice, multiplicative factors of the prior samples that are stored in memory MF. Predictor PR constructs the prediction of the current sample, using both the prediction coefficients PCT and a parameter D, which is a measure of a delay of the current sample with respect to the prior samples, used for computing the prediction. The frame is assembled in formatter FT similarly to the encoder of Fig. 1. However, in this case the signal SWT signifying the use of the prediction is also sent to the formatter for each subband, as well as prediction coefficients PCT and delay parameter D, if the prediction is operative. Ideally, delay parameter D is chosen so that it best approximates the period of the harmonic component where most of the power of the subband signal is concentrated. In order to better understand the meaning of that parameter, it is now made reference to Fig. 5, where an exemplary fragment of the waveshape of a subband signal is shown. According to the literature, the prediction X'(n) of the current sample is obtained as a weighted average of the N most recent prior samples: X'(n) = a0 * X(n) + a1 * X(n-1) + aN * X(n-N+1) where the weighting is made by means of as many prediction coefficients, computed in a way that minimizes the prediction error in the signal window which must be predicted. According to the principles of the invention, prediction X'(n) is also computed on the basis of N prior samples, but these samples ar chosen at a distance or interval D, D+1, ... , D+N-1 from the current sample, D being the above mentioned delay parameter: X'(n) = a0 * X(n-D) + a1 * X(n-D-1) + aN * X(n-D-N+1), where delay parameter D is also computed in a way that minimizes the prediction error. The reason for basing the prediction on a delayed signal resides in the pseudoperiodic nature of many audio signals, and, among these, a class of interest is musical signals. The periodicity features of the signal are emphasized by the breakdown into subbands: if a harmonic signal is considered, such as emitted by most musical instruments, if the subbands are narrow enough, a low number of harmonics will fall into each subband, and the signal will tend to be sinusoidal. It is therefore apparent that, in these conditions, it is more suitable to use, as a basis for prediction, the coefficients which are co-positioned to the current one in the prior period, rather than those immediately adjacent, which have generally a low correlation. Since the signals commonly regarded as "noise" have no periodicity features and have a low correlation, in implementing an encoding system for generic signals, it is preferable to have the possibility of inhibiting the prediction, so that the operation of the system with respect to the prior art is never at a disadvantage. The delay parameter D can be determined in several ways. In the most elementary case, D can be established at a constant value, equal to the center frequency in each subband. In this case, if desired, the incorporation of the values of parameter D in the frame may be dispensed with. In a more sophisticated embodiment of the process, parameter D is determined by computing the prediction error, in the window under consideration, with a plurality of delay intervals starting from a predetermined minimum value (in practice, 1) up to a predetermined maximum value, and by choosing for the coding the value that gives rise to the minimum prediction error. Another method of determining parameter D consists in computing the auto-correlation function of the signal window under consideration, within a variability range of D, and in choosing the value of D corresponding the the maximum of the auto-correlation function. Switch SW1 is switched by bit allocator BA so that signal SB is routed to subsequent processing, rather than residue RES, whenever prediction is not advantageous for encoding: in fact, the prediction coefficients and the delay parameter must be transmitted to the decoder if the decoder is to correctly reconstruct the signal, and, where the prediction does not reduce the signal entropy, they would merely cause a waste of bits. Switch SW2 is driven parallelly to SW1, and it also cuts out prediction whenever it is not advantageous, so that the prediction error RES is computed by using only information available to the decoder. The decoder, shown in Fig. 4, is substantially similar to the lower branch of the diagram of Fig. 3, except that the signal must eventually be fed to a bank of synthesizing filters FS. A second preferred embodiment of the invention is shown on Fig. 6. This embodiment differs from the first one in having a block IN at the input of memory MF. Block IN comprises an oversampling interpolator as described in Oppenheim and Shafer, implemented according to techniques known in the art, and allowing the number of samples per unit of time to be made denser without altering signal content. With this feature, which allows the prediction to be made from an oversampled signal, a more accurate positioning of the delay can be obtained, since the resolution is increased by the oversampling factor. Obivously, in this embodiment, the size of memory MF increases with the chosen oversampling factor. The same object can also be attained by connecting the interpolator downstream of memory MF, as shown on Fig. 8. In this case, block IN can be an interpolator of a more general type, e.g. of mathematical type, i.e., defined by an interpolation function that is evaluated in the required point, as a function of the delay. The delay may now take fractional values. The memory size need not be increased with this embodiment, but a larger computing power may be required. In both cases, the decoder (Figs. 7 and 9) needs no additional information, but must include the same block IN, in order to be able to reconstruct the signal with the same accuracy of the encoder. A few preferred embodiments of the invention have been disclosed. However, many other changes and modifications, obvious for the person skilled in the art, fall within the scope of the invention.

Claims: Process for encoding an input digital audio signal (SIG) by breaking down into a plurality of frequency subbands and requantization according to a predetermined perceptual model, and for delivering an output digital audio signal in form of a sequence of frames, each containing information on the course of each subband within a predetermined time window, characterized in that residues are formed by subtracting from said subbands in each window, respective predictions, said respective predictions are reconstructed from the requantized signals by means of a weighted average of a plurality of samples preceding in time by respective, delay intervals chosen for each subband, said residues formed are requantized and said requantized residues (RSB) and said prediction coefficients (PCT, D) are packed together to form said frames. The coding process of claim 1, characterized in that each of said delay intervals is determined, for each subband in each window, by computing the residue with a plurality of delay intervals, starting from a predetermined minimum value up to a predetermined maximum value, and choosing for the encoding the value causing the largest reduction of redundancy. The coding process of claim 1, characterized in that each of said delay intervals is determined, for each subband in each window, by computing the auto-correlation function of the signal in the window as a function of the delay interval, and choosing for the encoding the value for which the autocorrelation function is at a maximum. The coding process of one of claims 1 to 3, characterized in that said delay intervals are also packed into the frames. The coding process of one of claims 1 to 4, characterized in that the predictions are computed from an oversampled version of the signal. The coding process of one of claims 1 to 4, characterized in that , in the computation of the predictions, fractional values are accepted, and the samples used for constructing the predictions are obtained by interpolation, depending on the value of the fractional part of the delay. The coding process of one of claims 1 to 6, characterized in that , for each subband in each window, the information contents of the residue and of the subband signals are compared and, if the subband signal has a lower information content, the latter is requantized rather than the residue, and a code signifying such fact is packed into the frame. Encoder for digital audio signals, including a filterbank (FA) for breaking down said digital audio signals (SIG) into a plurality of frequency subbands (SB), a quantizer (QU) for receiving subband signals and requantizing them under control of a bit allocator (BA) governed by a predetermined perceptual model in order to remove irrelevant information from the subband signals, and a formatter (FT) which receives the quantizer's output signals and packs them in frames, characterized in that the encoder further includes circuit means (IQ, IS, SO2, MF, CP, RP) for receiving the quantizer's output (RSB) and reconstructing predictions of the current sample as a weighted average of a plurality of samples preceding in time by a delay interval chosen for each subband within a window, and an adder (SO1) receiving the outputs of the breakdown filterbank (FA) and the predictions (PRC) and generating a residue (RES) as difference which is fed to the quantizer (QU), and in that said formatter (FT) includes the value of said delay interval (D) in the frames. The digital audio signal encoder of claim 8, characterized in that said circuit means includes a memory (MF) receiving at its input the data generated by an inverse quantization chain (IQ, IS) driven by the quantizer's output, and predictor means (CP, PR) using the data stored in memory to generate the predictions. The digital audio signal encoder of claim 8 or 9, characterized in that it further comprises a switch (SW1) driven to cut out said adder (SO1) and to feed the current sample directly to the quantizer whenever sai circuit means determines that the encoding of the residue (RES) requires a number of bits larger than the encoding of the current sample. The digital audio signal encoder of one of claims 8 to 10, characterized in that it further comprises an interpolator receiving said signals at the output of the inverse quantization chain for computing a prediction corresponding to a fractional delay.

Inventors: DIMINO GIORGIO, DIMINO, GIORGIO
Applicants: RAI RADIOTELEVISIONE ITALIANA, RAI RADIOTELEVISIONE ITALIANA (S.P.A.)
Application year: 1994
Main classification: H04L9
IPC codes: H04B1, G10L19